Veterans' Lung Cancer Risk Conceptualizations versus Lung Cancer Screening Shared Decision-Making Conversations with Clinicians: A Qualitative Study.

Background: The Veterans Health Administration (VA) recommends lung cancer screening (LCS), including shared decision making between clinicians and veteran patients. We sought to characterize 1) veteran conceptualization of lung cancer risk and 2) veteran and clinician accounts of shared decision-making discussions about LCS to assess whether they reflect veteran concerns.

Methods: We conducted qualitative interviews at 6 VA sites, with 48 clinicians and 34 veterans offered LCS in the previous 6 mo.

Clinician contributions to central nervous system-active polypharmacy among older adults with dementia in the United States.

Background: Exposure to central nervous system (CNS)-active polypharmacy-overlapping exposure to three or more CNS-active medications-is potentially harmful yet common among persons living with dementia (PLWD). The extent to which these medications are prescribed to community-dwelling PLWD by individual clinicians versus distributed across multiple prescribers is unclear.

Methods: We identified community-dwelling Medicare beneficiaries with a dementia diagnosis and Medicare Parts A, B, and D coverage for at least one month in 2019.

Adaptation of a Tailored Lung Cancer Screening Decision Aid for People With HIV.

Background: People with HIV are both at elevated risk of lung cancer and at high risk of multimorbidity, which makes shared decision-making (SDM) for lung cancer screening (LCS) in people with HIV complex. Currently no known tools have been adapted for SDM in people with HIV.

Research Question: Can an SDM decision aid be adapted to include HIV-specific measures with input from both people with HIV and their providers?

Study Design And Methods: This study used qualitative methods including focus groups of people with HIV and interviews with HIV care providers to adapt and iterate an SDM tool for people with HIV.

The American Cancer Society National Lung Cancer Roundtable strategic plan: Current challenges and future directions for shared decision making for lung cancer screening.

Shared decision making (SDM) between health care professionals and patients is essential to help patients make well informed choices about lung cancer screening (LCS). Patients who participate in SDM have greater LCS knowledge, reduced decisional conflict, and improved adherence to annual screening compared with patients who do not participate in SDM. SDM tools are acceptable to patients and clinicians.

The Development and Performance of Alternative Criteria for Lung Cancer Screening.

Background: The recommendation for lung cancer screening (LCS) developed by the U.S. Preventive Services Task Force (USPSTF) may exclude some high-benefit people.

The Use of a Tailored Decision Aid to Improve Understanding of Lung Cancer Screening in People With HIV.

Background: People with HIV are at increased risk for lung cancer and multimorbidity, complicating the balance of risks and benefits of lung cancer screening. We previously adapted Decision Precision (screenlc.com) to guide shared decision-making for lung cancer screening in people with HIV.

Patient Perspectives on a Patient-Facing Tool for Lung Cancer Screening.

Background: Individuals with high risk for lung cancer may benefit from lung cancer screening, but there are associated risks as well as benefits. Shared decision-making (SDM) tools with personalized information may provide key support for patients. Understanding patient perspectives on educational tools to facilitate SDM for lung cancer screening may support tool development.

Prediction-Augmented Shared Decision-Making and Lung Cancer Screening Uptake.

Importance: Addressing poor uptake of low-dose computed tomography lung cancer screening (LCS) is critical, especially for those having the most to gain-high-benefit persons with high lung cancer risk and life expectancy more than 10 years.

Objective: To assess the association between LCS uptake and implementing a prediction-augmented shared decision-making (SDM) tool, which enables clinicians to identify persons predicted to be at high benefit and encourage LCS more strongly for these persons.

Design, Setting, And Participants: Quality improvement interrupted time series study at 6 Veterans Affairs sites that used a standard set of clinical reminders to prompt primary care clinicians and screening coordinators to engage in SDM for LCS-eligible persons.

Lung Cancer Screening Before and After a Multifaceted Electronic Health Record Intervention: A Nonrandomized Controlled Trial.

Importance: Lung cancer is the deadliest cancer in the US. Early-stage lung cancer detection with lung cancer screening (LCS) through low-dose computed tomography (LDCT) improves outcomes.

Objective: To assess the association of a multifaceted clinical decision support intervention with rates of identification and completion of recommended LCS-related services.

Clinician Perceptions on Using Decision Tools to Support Prediction-Based Shared Decision Making for Lung Cancer Screening.

Background: Considering a patient's full risk factor profile can promote personalized shared decision making (SDM). One way to accomplish this is through encounter tools that incorporate prediction models, but little is known about clinicians' perceptions of the feasibility of using these tools in practice. We examined how clinicians react to using one such encounter tool for personalizing SDM about lung cancer screening (LCS).

"It Can't Hurt!": Why Many Patients With Limited Life Expectancy Decide to Accept Lung Cancer Screening.

Purpose: Lung cancer screening (LCS) has less benefit and greater potential for iatrogenic harm among people with multiple comorbidities and limited life expectancy. Yet, such individuals are more likely to undergo screening than healthier LCS-eligible people. We sought to understand how patients with marginal LCS benefit conceptualize their health and make decisions regarding LCS.

Tackling Guideline Non-concordance: Primary Care Barriers to Incorporating Life Expectancy into Lung Cancer Screening Decision-Making-A Qualitative Study.

Background: Primary care providers (PCPs) are often the first point of contact for discussing lung cancer screening (LCS) with patients. While guidelines recommend against screening people with limited life expectancy (LLE) who are less likely to benefit, these patients are regularly referred for LCS.

Objective: We sought to understand barriers PCPs face to incorporating life expectancy into LCS decision-making for patients who otherwise meet eligibility criteria, and how a hypothetical point-of-care tool could support patient selection.

Considerations for using predictive models that include race as an input variable: The case study of lung cancer screening.

Indiscriminate use of predictive models incorporating race can reinforce biases present in source data and lead to an exacerbation of health disparities. In some countries, such as the United States, there is therefore a push to remove race from prediction models; however, there are still many prediction models that use race as an input. Biomedical informaticists who are given the responsibility of using these predictive models in healthcare environments are likely to be faced with questions like how to deal with race covariates in these models.

What Goes into Patient Selection for Lung Cancer Screening? Factors Associated with Clinician Judgments of Suitability for Screening.

Achieving the net benefit of lung cancer screening (LCS) depends on optimizing patient selection. To identify factors associated with clinician assessments that a patient was unlikely to benefit from LCS ("LCS-inappropriate") because of comorbidities or limited life expectancy. Retrospective analysis of patients assessed for LCS at 30 Veterans Health Administration facilities from January 1, 2015 to February 1, 2021.

Methods for Using Race and Ethnicity in Prediction Models for Lung Cancer Screening Eligibility.

Importance: Using race and ethnicity in clinical prediction models can reduce or inadvertently increase racial and ethnic disparities in medical decisions.

Objective: To compare eligibility for lung cancer screening in a contemporary representative US population by refitting the life-years gained from screening-computed tomography (LYFS-CT) model to exclude race and ethnicity vs a counterfactual eligibility approach that recalculates life expectancy for racial and ethnic minority individuals using the same covariates but substitutes White race and uses the higher predicted life expectancy, ensuring that historically underserved groups are not penalized.

Design, Setting, And Participants: The 2 submodels composing LYFS-CT NoRace were refit and externally validated without race and ethnicity: the lung cancer death submodel in participants of a large clinical trial (recruited 1993-2001; followed up until December 31, 2009) who ever smoked (n = 39 180) and the all-cause mortality submodel in the National Health Interview Survey (NHIS) 1997-2001 participants aged 40 to 80 years who ever smoked (n = 74 842, followed up until December 31, 2006).

Engaging Operational Partners Is Critical for Successful Implementation of Research Products: a Coincidence Analysis of Access-Related Projects in the Veterans Affairs Healthcare System.

Background/objective: The Veterans Health Administration (VHA) has prioritized timely access to care and has invested substantially in research aimed at optimizing veteran access. However, implementing research into practice remains challenging. Here, we assessed the implementation status of recent VHA access-related research projects and explored factors associated with successful implementation.

Implementation of Lung Cancer Screening in Primary Care and Pulmonary Clinics: Pragmatic Clinical Trial of Electronic Health Record-Integrated Everyday Shared Decision-Making Tool and Clinician-Facing Prompts.

Background: Although low-dose CT (LDCT) scan imaging lung cancer screening (LCS) can reduce lung cancer mortality, it remains underused. Shared decision-making (SDM) is recommended to assess the balance of benefits and harms for each patient.

Research Question: Do clinician-facing electronic health record (EHR) prompts and an EHR-integrated everyday SDM tool designed to support routine incorporation of SDM into primary care improve LDCT scan imaging ordering and completion?

Study Design And Methods: A preintervention and postintervention analysis was conducted in 30 primary care and four pulmonary clinics for visits with patients who met United States Preventive Services Task Force criteria for LCS.

CBK model composition using paired web services and executable functions: A demonstration for individualizing preventive services.

Introduction: Learning health systems are challenged to combine computable biomedical knowledge (CBK) models. Using common technical capabilities of the World Wide Web (WWW), digital objects called Knowledge Objects, and a new pattern of activating CBK models brought forth here, we aim to show that it is possible to compose CBK models in more highly standardized and potentially easier, more useful ways.

Methods: Using previously specified compound digital objects called Knowledge Objects, CBK models are packaged with metadata, API descriptions, and runtime requirements.

Achieving greater value for veterans through full cost transparency in primary care.

The COVID-19 pandemic has led to increased use of telephone and video encounters in the Veterans Health Administration and many other healthcare systems. One important difference between these virtual modalities and traditional face-to-face encounters is the different cost-sharing, travel costs, and time costs that patients face. Making the full costs of different visit modalities transparent to patients and their clinicians can help patients obtain greater value from their primary care encounters.

Planning and Reporting Effective Web-Based RAND/UCLA Appropriateness Method Panels: Literature Review and Preliminary Recommendations.

Background: The RAND/UCLA Appropriateness Method (RAM), a variant of the Delphi Method, was developed to synthesize existing evidence and elicit the clinical judgement of medical experts on the appropriate treatment of specific clinical presentations. Technological advances now allow researchers to conduct expert panels on the internet, offering a cost-effective and convenient alternative to the traditional RAM. For example, the Department of Veterans Affairs recently used a web-based RAM to validate clinical recommendations for de-intensifying routine primary care services.

Factors Associated With Declining Lung Cancer Screening After Discussion With a Physician in a Cohort of US Veterans.

Importance: Lung cancer screening (LCS) is underused in the US, particularly in underserved populations, and little is known about factors associated with declining LCS. Guidelines call for shared decision-making when LCS is offered to ensure informed, patient-centered decisions.

Objective: To assess how frequently veterans decline LCS and examine factors associated with declining LCS.